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Climora AI — Cleaner Commutes for BharatClimora AI — Cleaner Commutes for Bharat

The decision framework

PEBA

Population Exposure Burden Avoided

One score that ranks any intervention — a freight reroute, a school buffer, a fleet policy — by how much human exposure burden it removes. Cities and enterprises use PEBA the way lenders use a credit score: to decide.

PEBA score · example

freight reroute · ward-31

92

±3

94% model confidencetraces to Exposure × Population × Vulnerability × Time

0–25Marginallow burden avoided — deprioritize
26–50Moderatesituational value
51–75Strongfund when capacity allows
76–100Criticalhighest health return — act first

What can you do with PEBA?

Five decisions the score was built to make.

Budget prioritization

Defend every rupee with avoided burden

Rank clean-air and adaptation spending by health return. PEBA turns a budget line into a defensible statement: this allocation avoids this much exposure burden, for these people.

₹ per exposure-hour avoided

Health burden reduction

Target the burden, not the average

Find the wards, corridors, and hours where exposure concentrates on the vulnerable — and act there first. Equal AQI does not mean equal harm.

−18.4k exposure-hrs/day · top action

Smart city intervention planning

A ranked queue, not a wish list

Freight rerouting, school buffers, transit priority, greening — every candidate intervention scored on one comparable scale before capital is committed.

144 wards · one decision queue

Scope 3 decision support

Choose actions boards can stand behind

Score commute, fleet, and logistics interventions by emissions and human impact together — and report the difference in BRSR / CSRD-compatible terms.

emissions × exposure, one score

Public health impact

Evidence that survives review

Attribute burden to geography and source with documented methods — the evidence base for targeted programs, advisories, and grant applications.

WHO-aligned exposure-response

Have a decision PEBA should make?

Bring us a budget, a corridor, or a policy question.

Four dimensions, one score

01

Exposure

Pollutant concentration experienced by people — not at the monitor, but where they actually are, hour by hour.

02

Population

How many people occupy the exposed space and time — residents, commuters, workers, students.

03

Vulnerability

Who they are: age, health status, occupation, and socioeconomic capacity to avoid or recover from exposure.

04

Time

Duration and timing of exposure — a peak-hour corridor and a quiet night street are different problems.

Methodology, openly documented

PEBA is built to survive procurement diligence and peer review. Every score traces back to named data sources and documented models:

  • Exposure surfaces from fused satellite, ground monitor, and mobility data
  • Population presence modeled from census, mobility, and land-use signals
  • Vulnerability indices from demographic and health-capacity indicators
  • Burden estimation aligned with WHO exposure-response functions
  • Intervention scoring: counterfactual burden with vs. without action
ExplainableTraceable to sourceAuditable calculationsProcurement-readyCommittee-review ready

The PEBA brief

Take the framework to your team.

A concise document covering the PEBA model, methodology, and worked examples — written to be shared with committees, boards, and procurement teams.